Cerebrospinal Fluid Biomarkers Profiling in Cerebral Amyloid Angiopathy and Relationship With Disease Phenotypes
Mattia Losa, Matteo Cotta Ramusino, Isabella Cama, Lorenzo Gualco, Ilaria Gandoglia, Federico Massa, Andrea Donniaquio, Pierumberto Mortola, Lucia Argenti, Lorenzo Lombardo, Wendy Kreshpa, Virginia Pelagotti, Giulia Bozzo, Beatrice Orso, Pietro Mattioli, Dario Arnaldi, A. Cirone, Shahzad Ali, Mehrnaz Hamedani, Martina Pulze, Domenico Plantone, Luigi Lorenzini, Laura Falcitano, Federico Mazzacane, Giulia Perini, Alfredo Costa, Michele Piana, Lucio Castellan, Antonio Uccelli, Angelo Schenone, Mariel G. Kozberg, Fabrizio Piazza, Massimo Del Sette, Sara Garbarino, Luca Roccatagliata, Lisa Maria Farina, Matteo Pardini
Abstract
Background Cerebral amyloid angiopathy (CAA) is a heterogeneous small vessel disease that can occur independently or alongside Alzheimer disease (AD). CAA is diagnosed using the Boston Criteria 2.0, integrating clinical and neuroimaging features, whereas the Cerebrospinal Fluid (CSF) role in clinical practice remains under investigation. This study explores whether CSF biomarkers can identify distinct disease phenotypes, supporting hemorrhagic risk stratification. Methods We enrolled probable patients with CAA retrospectively (Boston Criteria 2.0) from 2 institutions, collecting clinical, neuroimaging, and follow‐up data alongside core CSF biomarkers (Aβ40 [amyloid β 1–40], Aβ42 [amyloid β 1–42], p‐Tau181 [phosphorylated Tau], total‐Tau). Patients with CAA were stratified applying the Amyloid Tau Neurodegeneration (ATN) research framework, according to the presence of CSF amyloidosis (A + CAA versus A − CAA) and tauopathy (A + T + CAA versus A + T − CAA), and using unsupervised clustering, which defined CAA subgroups based on CSF biomarker levels only. Kaplan‐Meier and Cox regression analyses assessed the predictive value of CSF‐based subgroups for symptomatic hemorrhages during follow‐up. Results Seventy‐one probable CAA patients (aged 71.77±8.45 years, 66% men, median follow‐up 1.15 years [0.50–2.44]) were enrolled. A + CAA showed a higher prevalence of cortical superficial siderosis than A − CAA (67% versus 25%, P =0.016). A + T − CAA had a greater hemorrhagic risk than A + T + CAA during follow‐up (29 versus 7 events per 100 patient‐years, P =0.010; log‐rank test: P =0.013). Unsupervised clustering identified 2 subgroups, which we defined as pure CAA and CAA‐ADA, with pure CAA presenting more symptomatic hemorrhages during follow‐up (22 versus 0 events per 100 patient‐years, P =0.017; log‐rank test, P =0.011). Conclusions CSF‐based profiling effectively stratifies CAA phenotypes, offering a promising prognostic tool alongside neuroimaging markers. Further validation is needed to confirm its role in identifying patients with CAA with different natural histories.